Shared decision-making (SDM), defined as active patient participation during health care visits, is widely promoted in the literature and medical school curricula as an ideal model for health care decision-making. There is evidence that SDM improves health outcomes, but studies show that attempts to increase SDM have resulted in greater anxiety and dissatisfaction for some patients. The effects of SDM are likely dependent on how much patients want to participate. Older patients, in particular, are less likely to want to participate in making important medical decisions. In order to promote optimal patient-centered care for older patients, it is essential that what drives their preferences for participation in health care visits be understood. The overall goal of this project is to determine how personal characteristics and past experiences with decision-making influence both preferences for participation in health care visits and proactive behaviors related to health care decisions for older patients. Specifically, this project will: (1) categorize older adults into types based on preferences for participation; (2) relate these preference types to personal characteristics (i.e., capacity to make decisions and long-standing psychological traits), to previous experiences with decision making (health care and non-health care related), and to previous experiences with a specific health care provider; and (3) relate proactive decision-related behaviors, including health information seeking on the Internet and completion of advance directives (e.g., living wills), to personal characteristics and previous experiences. We will build on the Wisconsin Longitudinal Study (WLS) which, for 47 years, has followed over 10,000 men and women who graduated from Wisconsin high schools in 1957. Respondents are currently 64-65 years old and have completed extensive telephone and mail surveys with high sample retention over time. Included in the current survey round are items on health care decision-making preferences and behaviors. Cluster analysis will be used to characterize preference types, and multivariate logistic regression will be used to relate preference types and behaviors to personal characteristics and experiences. Preferences and behaviors will also be examined in a number of AHRQ-defined priority populations, including persons with low income, poor health, or chronic illness, persons living in rural areas, and women. The proposed research will provide valuable information for promoting optimal patient-centered care to clinicians, policymakers, and researchers.